Triple
T12517320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple Partition Map |
E299220
|
entity |
| Predicate | partitionEntryType |
P44366
|
FINISHED |
| Object | fixed-size entries in a partition map area |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: fixed-size entries in a partition map area | Statement: [Apple Partition Map, partitionEntryType, fixed-size entries in a partition map area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partitionEntryType Context triple: [Apple Partition Map, partitionEntryType, fixed-size entries in a partition map area]
-
A.
partitionScheme
Indicates how a whole is divided into distinct parts or segments according to a specific organizing scheme.
-
B.
typicalEntryType
chosen
Indicates the usual or standard category or kind of entry associated with something.
-
C.
partCType
Indicates that an entity is classified as a specific subtype or category of a larger part or component.
-
D.
partBType
Indicates that one entity is classified as the type or category to which the second entity (part B) belongs.
-
E.
partitionIVContent
Indicates that one entity divides another entity’s content into distinct parts or sections.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d954b867dc8190af8a70f797e4d133 |
completed | April 10, 2026, 7:51 p.m. |
| PD | Predicate disambiguation | batch_69d954096af88190b6be81b008c82139 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:57 p.m.